发现我们为 deployment & devops 精心策划的 MCP 服务器集合。浏览 2341 个服务器,找到满足您需求的完美 MCP。
Generates data pipeline code for any Airbyte Connector using a single natural language prompt.
Simplifies the management of multiple Model Context Protocol (MCP) servers through a command-line interface.
Automate Looker workflows, CI pipelines, and AI-assisted LookML development with a lightweight CLI and MCP server.
Connects AI assistants to Infrahub, enabling agents to read and modify infrastructure state through a standardized, audited interface.
Implements a system-wide Model Context Protocol server offering file operations, HTTP requests, and command execution.
Provides comprehensive system information and management capabilities for Linux servers through MCP and HTTP REST APIs, enabling AI agents to monitor and interact with server resources.
Ensures AI-generated code is production-ready by enforcing quality guardrails and deployability standards.
Enables programmatic interaction with Expo projects and Expo Application Services (EAS) for mobile app development automation.
Enforces standardized development rules and context for Business Central projects.
Enables AI models to gain full control over Mailcow email servers via the Model Context Protocol.
Integrates SAP Business One with Microsoft Copilot Studio via the Model Context Protocol (MCP) to enable conversational AI interactions.
Transforms any shell command into an AI-callable Model Context Protocol (MCP) server tool using simple YAML configurations.
Deploys an integrated environment for Alfresco Community, an MCP server with Markdown tools, and a FastAPI agent utilizing LlamaIndex for AI-driven content interaction.
Transforms penetration testing into an intelligent, automated, and secure process.
Executes command-line commands and returns their output, status code, and errors.
Integrates AI agents with Commvault environments to manage job details, commcell metrics, client and storage information, user permissions, plan configurations, and backup schedules.
Provides a Dockerized web-based desktop environment with a Playwright server for robust browser automation.
Executes code in isolated Docker containers and returns the results to language models.
Provides a Model Context Protocol (MCP) server implementation for fetching data from Talos nodes.
Enables AI assistants to interact with Docker via the Model Context Protocol (MCP).
Scroll for more results...